Papers
Additional bibliographic information can be found at DBLP and Google Scholar.- A. Netti, Z. Kiziltan, O. Babaoglu, A. Sirbu, A. Bartolini, A. Borghesi. A Machine Learning Approach to Online Fault Classification in HPC Systems. In Future Generation Computing Systems, Elsevier, vol. 110, September 2020.
- C. Galleguillos, Z. Kiziltan, A. Sirbu, O. Babaoglu. Constraint Programming-based Job Dispatching for Modern HPC Applications. In Proceedings of the International Conference on Principles and Practice of Constraint Programming (CP 2019), Stamford, CT, USA, September 2019.
- A. Netti, Z. Kiziltan, O. Babaoglu, A. Sirbu, A. Bartolini, A. Borghesi. Online Fault Classification in HPC Systems through Machine Learning. In Proceedings of Euro-Par 2019: European Conference on Parallel Processing, Ramin Yahyapour (Ed.), Lecture Notes in Computer Science, vol. 11725, August 2019.
- A. Netti, Z. Kiziltan, O. Babaoglu, A. Sirbu, A. Bartolini, A. Borghesi. FINJ: A Fault Injection Tool for HPC Systems. In Proceedings of Euro-Par 2018: European Conference on Parallel Processing 11th Workshop on Resiliency in High Performance Computing (Resilience 2018), G. Mencagli, D. B. Heras et al. (Eds.), Lecture Notes in Computer Science, vol. 11339, August 2018.
- O. Babaoglu, A. Sirbu. Cognified Distributed Computing. In Proceedings of the 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018), Vienna, Austria, July 2018. The final publication is available at ieeexplore.ieee.org (DOI 10.1109/ICDCS.2018.00118)
- A. Netti, C. Galleguillos, Z. Kiziltan, A. Sirbu, O. Babaoglu. Heterogeneity-aware Resource Allocation in HPC Systems. In High Performance Computing. ISC High Performance 2018, Yokota R., Weiland M., Keyes D., Trinitis C. (Eds.) Lecture Notes in Computer Science, vol 10876, Springer-Verlag, Berlin, 2018. ( DOI 10.1007/978-3-319-92040-5_1)
- A. Sirbu, O. Babaoglu. A Data-Driven Approach to Modeling Power Consumption for a Hybrid Supercomputer. In Concurrency and Computation: Practice and Experience, January 2018 (DOI 10.1002/cpe.4410).
- C. Galleguillos, A. Sirbu, Z. Kiziltan, O. Babaoglu, A. Borghesi, T. Bridi. Data-driven job dispatching in HPC systems. In Proceedings of the Third International Workshop on Machine Learning, Optimization, and Big Data (MOD 2017), Springer, Cham, 2017.
- A. Balliu, D. Olivetti, O. Babaoglu, M. Marzolla, A. Sirbu. A Big Data Analyzer for Large Trace Logs. Springer Computing, vol. 98, no. 12, December 2016. The final publication is available at link.springer.com (DOI 10.1007/s00607-015-0480-7)
- A. Sirbu, O. Babaoglu. Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer. In Proceedings of Euro-Par 2016, Grenoble, France, August 2016.
- A. Sirbu, O. Babaoglu. Predicting System-level Power for a Hybrid Supercomputer. arXiv:1605.09530 [cs.DC], May 2016. In Proceedings of International Conference on High Performance Computing & Simulation (HPCS 2016), Innsbruck, Austria, July 2016.
- A. Sirbu, O. Babaoglu. Towards Operator-less Data Centers Through Data-Driven, Predictive, Proactive Autonomics. Cluster Computing vol. 19, no. 2, April 2016. The final publication is available at link.springer.com (DOI 10.1007/s10586-016-0564-y)
- A. Sirbu, O. Babaoglu. A Holistic Approach to Log Data Analysis in High-Performance Computing Systems: The case of IBM BlueGene/Q. In Proceedings of Euro-Par 2015: Parallel Processing Workshops, Hunold, S. et al. (Eds.), Lecture Notes in Computer Science vol. 9523, Springer-Verlag, Berlin, 2015. The final publication is available at link.springer.com (DOI 10.1007/978-3-319-27308-2_51)
- A. Sirbu, O. Babaoglu. Towards Data-Driven Autonomics in Data Centers. In Proceedings of IEEE International Conference on Cloud and Autonomic Computing (ICCAC), Boston, Massachusetts. September 2015. The final publication is available at ieeexplore.ieee.org (DOI 10.1109/ICCAC.2015.19)
- O. Babaoglu, M. Marzolla. The people's cloud. IEEE Spectrum, vol. 51, no. 10, October 2014.
© ACM Copyright Notice: Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee.
© IEEE Copyright Notice: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.